Comparative safety and effectiveness of Pfizer BA.4-5 versus Sanofi during the spring 2023 COVID-19 booster vaccination programme in England: a matched cohort study in OpenSAFELY-TPP (preprint)

Introduction: The spring 2023 COVID-19 booster vaccination programme in England used both Pfizer BA.4-5 and Sanofi vaccines. All people aged 75 years or over and the clinically vulnerable were eligible to receive a booster dose. Direct comparisons of the effectiveness of these two vaccines in boosting protection against severe COVID-19 events have not been made in trials or observational data. Methods With the approval of NHS England, we used the OpenSAFELY-TPP database to compare effectiveness of the Pfizer BA.4-5 and Sanofi vaccines during the spring 2023 booster programme, between 1 April and 30 June 2023. We investigated two cohorts separately: those aged 75 or over (75+); and those aged 50 or over and clinically vulnerable (CV). In each cohort, vaccine recipients were matched on date of vaccination, COVID-19 vaccine history, age, and other characteristics. Effectiveness outcomes were COVID-19 hospital admission, COVID-19 critical care admission, and COVID-19 death up to 16 weeks after vaccination. Safety outcomes were pericarditis and myocarditis up to 4 weeks after vaccination. We report the cumulative incidence of each outcome, and compare safety and effectiveness using risk differences (RD), relative risks (RR), and incidence rate ratios (IRRs). Results 492,642 people were 1-1 matched in the CV cohort, and 673,926 in the 75+ cohort, contributing a total of 7,423,251 and 10,173,230 person-weeks of follow-up, respectively. The incidence of COVID-19 hospital admission was higher for Sanofi than for Pfizer BA.4-5. In the CV cohort, 16-week risks per 10,000 people were 22.3 (95%CI 20.4 to 24.3) for Pfizer BA.4-5 and 26.4 (24.4 to 28.7) for Sanofi, with an IRR of 1.19 (95%CI 1.06 to 1.34). In the 75+ cohort, these were 17.5 (16.1 to 19.1) for Pfizer BA.4-5 and 20.4 (18.9 to 22.1) for Sanofi, with an IRR of 1.18 (1.05-1.32). These findings were similar across all pre-specified subgroups. More severe COVID-19 related outcomes (critical care admission and death), and safety outcomes at 4 weeks, were rare in both vaccines so we could not reliably compare effectiveness of the two vaccines. Conclusion This observational study comparing effectiveness of Pfizer BA.4-5 and Sanofi vaccine during the spring 2023 programme in England in the two main eligible cohorts - people aged 75 and over and in clinically vulnerable people - found some evidence of superior effectiveness against COVID-19 hospital admission for Pfizer BA.4-5 compared with Sanofi within 16 weeks after vaccination.

Changes in opioid prescribing during the COVID-19 pandemic in England: cohort study of 20 million patients in OpenSAFELY-TPP (preprint)

Background: The COVID-19 pandemic led to disruptions in healthcare delivery, including postponement of elective procedures and difficulty accessing in-person care, which may have increased the need for strong pharmacological pain relief in some patients. Methods: With NHS England approval, we used routine clinical data from >20 million general practice adult patients in OpenSAFELY-TPP. We used interrupted time series analysis to quantify trends in prevalent and incident opioid prescribing prior to the pandemic (January 2018-February 2020) and changes during the COVID-19 lockdown period (March 2020-March 2021) and recovery period (April 2021-June 2022). We identified how these changes varied in people living in care homes, and by age, sex, deprivation, ethnicity, and geographic region. Results: The median number of people prescribed an opioid per month was 50.9 per 1000 patients prior to the pandemic. We observed little change in overall prescribing after the start of the pandemic, except for a temporary increase in March 2020. There was a 9.8% (95%CI -14.5%, -6.5%) reduction in new opioid prescribing from March 2020, sustained to the end of the study period. Reductions in new prescribing were observed for all demographics except people 80+ years. Among care home residents, in April 2020 new opioid prescribing increased by 112.5% (95%CI 92.2%, 134.9%) and parenteral opioid prescribing increased by 186.3% (95%CI 153.1%, 223.9%). Conclusion: Changes in opioid prescribing during the COVID-19 pandemic were mostly consistent across subgroups with the exception of differences by age and care home residence. Among people in care homes, increases in parenteral opioid prescribing likely reflect use to treat end-of-life COVID-19 symptoms. Further research is needed to understand what is driving the reduction in new opioid prescribing and its relation to changes to health care provision during the pandemic.

The safety of antivirals and neutralising monoclonal antibodies used in prehospital treatment of Covid-19 (preprint)

Objective This proof-of-principle pharmacovigilance study used Electronic Health Record (EHR) data to examine the safety of sotrovimab, paxlovid and molnupiravir in prehospital treatment of Covid-19. Method With NHS England approval, we conducted an observational cohort study using OpenSAFELY-TPP, a secure software-platform which executes analyses across EHRs for 24 million people in England. High-risk individuals with Covid-19 eligible for prehospital treatment were included. Adverse events (AEs) were categorised into events in the drugs Summary of Product Characteristics (SmPC), drug-reactions and immune-mediated. Cox models compared risk across treatments. A pre-pandemic record analysis was performed for comparative purposes. Results Between 2021-2023, 37,449 patients received sotrovimab, paxlovid or molnupiravir whilst 109,647 patients made up an eligible-but-untreated population. The 29-day rates of AEs were low: SmPC 0.34 per 1000 patient-years (95% CI 0.32-0.36); drug-reactions 0.01 (95% CI 0.01-0.02) and immune-mediated 0.03 (95% CI 0.03-0.04), and similar or lower than the pre-pandemic period. Compared with the eligible but untreated population, sotrovimab and paxlovid associated with a risk of SmPC AE [adjHR 1.36 (95% CI 1.15-1.62) and 1.28 (95% CI 1.05-1.55), respectively], whilst sotrovimab associated with a risk of drug-reactions [adjHR 2.95 (95% CI 1.56-5.55)] and immune-mediated events [adjHR 3.22 (95% CI 1.86-5.57)]. Conclusion Sotrovimab, paxlovid and molnupiravir demonstrate acceptable safety profiles. Although the risk of AEs was greatest with sotrovimab, event rates were lower than comparative pre-pandemic period.

Healthcare utilisation in people with long COVID: an OpenSAFELY cohort study (preprint)

BackgroundLong COVID, characterised by various symptoms and complications, potentially increases healthcare utilisation and costs. However, its impact on the NHS remains to be determined. ObjectiveThis study aims to assess the healthcare utilisation of individuals with long COVID. MethodsWith the approval of NHS England, we conducted a matched cohort study using primary and secondary care data via OpenSAFELY, a platform for analysing anonymous electronic health records. The long COVID exposure group, defined by diagnostic codes, was matched with five comparators without long COVID between Nov 2020 and Jan 2023. We compared their total healthcare utilisation from GP consultations, prescriptions, hospital admissions, A&E visits, and outpatient appointments. Healthcare utilisation and costs were evaluated using a two-part model adjusting for covariates. Using a difference-in-difference model, we also compared healthcare utilisation after long COVID with pre-pandemic records. ResultsWe identified 52,988 individuals with a long COVID diagnosis, matched to 264,867 comparators without a diagnosis. In the 12 months post-diagnosis, there was strong evidence that those with long COVID were more likely to use healthcare resources (OR: 8.07, 95% CI: 7.54 - 8.64), and have 49% more healthcare utilisation (RR: 1.49, 95% CI: 1.47 - 1.50). Our model estimated that the long COVID group had 30 healthcare visits per year (predicted mean: 29.23, 95% CI: 28.58 - 29.92), compared to 16 in the comparator group (predicted mean visits: 16.04, 95% CI: 15.73 - 16.36). Individuals with long COVID were more likely to have non-zero healthcare expenditures (OR = 7.47, 95% CI = 7.02 - 7.95), with costs being 43% higher than the comparator group (cost ratio = 1.43, 95% CI: 1.38 - 1.49). The long COVID group costs approximately {pound}2,500 per person per year (predicted mean cost: {pound}2,562.50, 95% CI: {pound}2,335.60 - {pound}2,819.22), and the comparator group costs {pound}1,500 (predicted mean cost: {pound}1,527.43, 95% CI: {pound}1,404.33 - 1,664.45.) Historically, individuals with long COVID utilised healthcare resources more frequently, but their average healthcare utilisation increased more after being diagnosed with long COVID, compared to the comparator group. ConclusionLong COVID increases healthcare utilisation and costs. Public health policies should allocate more resources towards preventing, treating, and supporting individuals with long COVID.

Weight trends amongst adults with diabetes or hypertension during the COVID-19 pandemic: an observational study using OpenSAFELY (preprint)

AimsTo describe patterns of weight change amongst adults living in England with Type 2 Diabetes (T2D) and/or hypertension during the COVID-19 pandemic. Design and SettingWith the approval of NHS England, we conducted an observational cohort study using the routinely collected health data of approximately 40% of adults living in England, accessed through the OpenSAFELY service inside TPP. MethodWe estimated individual rates of weight gain during the pandemic ({delta}). We then estimated associations between clinical and sociodemographic characteristics and rapid weight gain (>0.5kg/m2/year) using multivariable logistic regression. ResultsWe extracted data on adults with T2D (n=1,231,455, 44% female, 76% white British) or hypertension (n=3,558,405, 50% female, 84% white British). Adults with T2D lost weight overall (median {delta} = -0.1kg/m2/year [IQR: -0.7, 0.4]), however, rapid weight gain was common (20.7%) and associated with sex (male vs female: aOR 0.78[95%CI 0.77, 0.79]); age, older age reduced odds (e.g. 60-69-year-olds vs 18-29-year-olds: aOR 0.66[0.61, 0.71]); deprivation, (least-deprived-IMD vs most-deprived-IMD: aOR 0.87[0.85, 0.89]); white ethnicity (Black vs White: aOR 0.70[0.69, 0.71]); mental health conditions (e.g. depression: aOR 1.13 [1.12, 1.15]); and diabetes treatment (non-insulin treatment vs no pharmacological treatment: aOR 0.68[0.67, 0.69]). Adults with hypertension maintained stable weight overall (median {delta} = 0.0kg/m2/year [-0.6, 0.5]), however, rapid weight gain was common (24.7%) and associated with similar characteristics as in T2D. ConclusionAmongst adults living in England with T2D and/or hypertension, rapid pandemic weight gain was more common amongst females, younger adults, those living in more deprived areas, and those with mental health conditions. How this fits inPrevious studies, in the general population, have reported female sex, deprivation and comorbid mental health conditions increased risk of unhealthy weight gain during the pandemic, but it is not clear whether people living with hypertensions and/or type 2 diabetes experienced the same trends. We found that, during the pandemic, adults with hypertension maintained a stable weight whilst those with type 2 diabetes lost weight overall. However, underlying these overall trends, rapid weight gain was common amongst people with type 2 diabetes (20.7%) or hypertension (24.7%)), with female sex, younger age, deprivation, and comorbid mental health conditions associated with an increased odds of rapid weight gain in both populations. We have identified clinical and sociodemographic characteristics of individuals with hypertension and/or type 2 diabetes who could benefit from primary care interventions on weight and health behaviours to combat health inequalities in patterns of weight gain that were exacerbated by the pandemic.

Ursodeoxycholic acid and severe COVID-19 outcomes in people with liver disease: a cohort study using the OpenSAFELY platform (preprint)

Biological evidence suggests ursodeoxycholic acid (UDCA) - a common treatment of cholestatic liver disease - may prevent severe COVID-19 outcomes. With the approval of NHS England, we conducted a population-based cohort study using primary care records, linked to death registration data and hospital records through the OpenSAFELY-TPP platform. We estimated the hazard of COVID-19 hospitalisation or death between 1 March 2020 and 31 December 2022, comparing UDCA treatment to no UDCA treatment in a population with indication. Of 11,320 eligible individuals, 642 were hospitalised or died with COVID-19 during follow-up, 402 (63%) events among UDCA users. After confounder adjustment, UDCA was associated with a 21% (95% CI 7%-33%) relative reduction in the hazard of COVID-19 hospitalisation or death, consistent with an absolute risk reduction of 1.3% (95% CI 1.0%-1.6%). Our findings support calls for clinical trials investigating UDCA as a preventative measure for severe COVID-19 outcomes.

Impact of COVID-19 on mental illness in vaccinated and unvaccinated people: a population-based cohort study in OpenSAFELY (preprint)

Background: COVID-19 is associated with subsequent mental illness in both hospital- and population-based studies. Evidence regarding effects of COVID-19 vaccination on mental health consequences of COVID-19 is limited. Methods: With the approval of NHS England, we used linked electronic health records (OpenSAFELY-TPP) to conduct analyses in a 'pre-vaccination' cohort (17,619,987 people) followed during the wild-type/Alpha variant eras (January 2020-June 2021), and 'vaccinated' and 'unvaccinated' cohorts (13,716,225 and 3,130,581 people respectively) during the Delta variant era (June-December 2021). We estimated adjusted hazard ratios (aHRs) comparing the incidence of mental illness after diagnosis of COVID-19 with the incidence before or without COVID-19. Outcomes: We considered eight outcomes: depression, serious mental illness, general anxiety, post-traumatic stress disorder, eating disorders, addiction, self-harm, and suicide. Incidence of most outcomes was elevated during weeks 1-4 after COVID-19 diagnosis, compared with before or without COVID-19, in each cohort. Vaccination mitigated the adverse effects of COVID-19 on mental health: aHRs (95% CIs) for depression and for serious mental illness during weeks 1-4 after COVID-19 were 1.93 (1.88-1.98) and 1.42 (1.24-1.61) respectively in the pre-vaccination cohort and 1.79 (1.68-1.91) and 2.21 (1.99-2.45) respectively in the unvaccinated cohort, compared with 1.16 (1.12-1.20) and 0.91 (0.84-0.98) respectively in the vaccinated cohort. Elevation in incidence was higher, and persisted for longer, after hospitalised than non-hospitalised COVID-19. Interpretation: Incidence of mental illness is elevated for up to a year following severe COVID-19 in unvaccinated people. Vaccination mitigates the adverse effect of COVID-19 on mental health. Funding: Medical Research Council (MC_PC_20059) and NIHR (COV-LT-0009).

The impact of Long COVID on Health-Related Quality-of-life using OpenPROMPT (preprint)

Background: Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. Methods With the approval of NHS England, we developed OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. Results We used data from 6,070 participants where 24.7% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a high probability of reporting loss in quality-of-life (OR: 22, 95% CI:12.35-39.29) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 60.2, 95% CI: 27.79-130.57) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. Conclusions We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease.

Clinical coding of long COVID in primary care 2020-2023 in a cohort of 19 million adults: an OpenSAFELY analysis (preprint)

Background Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe those with long COVID in primary care records in England. Methods With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. We calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and minimally adjusted rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. Findings We identified a total of 55,465 people recorded to have long COVID over the study period, with incidence of new long COVID records increasing steadily over 2021, and declining over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5-179) and 100.5 men (99.5-102). In terms of vaccination against COVID-19, the lowest rates were observed in those with 3+ vaccine doses (103.5 [95% CI: 101.5-105]). Finally, the majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 weeks before the long COVID record. Interpretation EHR recorded long COVID remains very low compared and incident records of long COVID declined over 2022. We found the lowest rates of recorded long COVID in people with 3 or more vaccine doses. We summarised several sources of possible bias for researchers using EHRs to study long COVID. Funding This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073))

Group A streptococcal cases and treatments during the COVID-19 pandemic and 2022 outbreak: a retrospective cohort study in England using OpenSAFELY-TPP (preprint)

ObjectiveTo investigate the impact of the COVID-19 pandemic on Group A streptococcal (GAS) cases and related antibiotic prescriptions. DesignA retrospective cohort study with supporting dashboards with the approval of NHS England. SettingPrimary care practices in England using TPP SystmOne software from January 2018 through March 2023. ParticipantsPatients included were those registered at a TPP practice for each month of the study period. Patients with missing sex or age were excluded, resulting in a population of 23,816,470 in January 2018, increasing to 25,541,940 by March 2023. Main outcome measuresWe calculated monthly counts and crude rates of GAS cases (sore throat/tonsillitis, scarlet fever, invasive group A strep) and prescriptions linked with a GAS case, before (pre-April 2020), during and after (post-April 2021) COVID-19 restrictions. We calculated the maximum and minimum count and rate for each season (years running September-August), and the rate ratio (RR) of the 2022/23 season to the last comparably high season (2017/18). ResultsRecording of GAS cases and antibiotic prescription linked with a GAS case peaked in December 2022, higher than the 2017/2018 peak. The peak rate of monthly sore throat/tonsillitis (possible group A strep throat) recording was 5.33 per 1,000 (RR 2022/23 versus 2017/18 1.39 (CI: 1.38 to 1.40)). Scarlet fever recording peaked at 0.51 per 1,000 (RR 2.68 (CI: 2.59 to 2.77)), and invasive group A streptococcal infection (iGAS) at 0.01 per 1,000 (RR 4.37 (CI: 2.94 to 6.48)). First line antibiotics with a record of a GAS infection peaked at 2.80 per 1,000 (RR 1.37 (CI:1.35 to 1.38)), alternative antibiotics at 2.03 per 1,000 (RR 2.30 (CI:2.26 to 2.34)), and reserved antibiotics at 0.09 per 1,000 (RR 2.42 (CI:2.24 to 2.61). For individual antibiotics, azithromycin with GAS indication showed the greatest relative increase (RR 7.37 (CI:6.22 to 8.74)).This followed a sharp drop in recording of cases and associated prescriptions during the period of COVID-19 restrictions where the maximum count and rates were lower than any pre COVID-19 minimum. More detailed demographic breakdowns can be found in our regularly updated dashboard report. ConclusionsRates of scarlet fever, sore throat/tonsillitis and iGAS recording and associated antibiotic prescribing peaked in December 2022. Primary care data can supplement existing infectious disease surveillance through linkages with relevant prescribing data and detailed clinical and demographic subgroups. What is knownDuring the COVID-19 pandemic there has been a substantial change to the pattern of circulating viruses and bacteria that cause illnesses. A spike in group A streptococcal infections in England starting December 2022 was associated with 426 deaths, including 48 children as of 7th May 2023. Increased demand for antibiotics in this period led to medicines shortages and the introduction of Serious Shortage Protocols (SSPs). Existing surveillance systems such as notifiable disease reports and GP in-hours surveillance bulletins describe clinical events, but they do not link to relevant prescribing data. What this study adds- This study supports the findings of routine surveillance reports which indicated a drop in GAS infections during the COVID-19 restrictions, followed by a spike in December 2022, demonstrating that the OpenSAFELY platform and primary care data can be used to rapidly describe not only clinical events but also relevant prescribing in the case of future outbreaks. - Antibiotic prescribing with a GAS indication, particularly for phenoxymethylpenicillin alternatives and reserved antibiotics, was higher in the December 2022 peak than in the 2017/2018 peak.

Effect of the 2022 COVID-19 booster vaccination campaign in 50 year olds in England: regression discontinuity analysis in OpenSAFELY (preprint)

Background: SARS-CoV-2 vaccines are highly effective in preventing severe COVID-19 but require boosting to maintain protection. Changes to circulating variants and prevalent natural immunity may impact on real-world effectiveness of boosters in different time periods and in different populations. Methods: With NHS England approval, we used linked routine clinical data from >24 million patients to evaluate the effectiveness of the 2022 combined COVID-19 autumn booster and influenza vaccine campaign in non-clinically vulnerable 50-year-olds in England using a regression discontinuity design. Our primary outcome was a composite of 6-week COVID-19 emergency attendance, COVID-19 unplanned hospitalisation, or death. The secondary outcomes were: respiratory hospitalisations or death; any unplanned hospitalisation; and any death. Results: Our study included 1,917,375 people aged 45-54 years with no evidence of being in a high-risk group prioritised for vaccination. By 26 November 2022, booster vaccine coverage was 11.1% at age 49.75 years increasing to 39.7% at age 50.25 years. The estimated effect of the campaign on the risk of the primary outcome in 50-year-olds during weeks 7-12 after the campaign start was -0.4 per 100,000 (95% CI -7.8, 7.1). For the secondary outcomes the estimated effects were: -0.6 per 100,000 (95%CI -13.5, 12.3) for respiratory outcomes; 5.0 per 100,000 (95%CI -40.7, 50.8) for unplanned hospitalisations; and 3.0 per 100,000 (95%CI -2.7, 8.6) for any death. The results were similar when using different follow-up start dates, different bandwidths, or when estimating the effect of vaccination (rather than the campaign). Conclusion: This study found little evidence that the autumn 2022 vaccination campaign in England was associated with a reduction in severe COVID-19-related outcomes among non-clinically vulnerable 50-year-olds. Possible explanations include the low risk of severe outcomes due to substantial pre-existing vaccine- and infection-induced immunity. Modest booster coverage reduced the precision with which we could estimate effectiveness. The booster campaign may have had effects beyond those estimated, including reducing virus transmission and incidence of mild or moderate COVID-19.

Fit notes associated with COVID-19 in 24 million patients' primary care records: A cohort study in OpenSAFELY-TPP (preprint)

Background: Fit notes ("sick notes") are issued by general practitioners (GPs) when a person can't work for health reasons and is an indication of the public health and economic burden for people recovering from COVID-19. Methods: With NHS England approval, we used routine clinical data from >24 million patients to compare fit note incidence in people 18-64 years with and without evidence of COVID-19 in 2020, 2021 and 2022. We fit Cox regression models to estimate adjusted hazard ratios, overall and by time post-diagnosis and within demographic subgroups. Results: We identified 365,421, 1,206,555 and 1,321,313 people with evidence of COVID-19 in 2020, 2021 and 2022. The fit note rate was 4.88 per 100 person-months (95%CI 4.83-4.93) in 2020, 2.66 (95%CI 2.64-2.67) in 2021, and 1.73 (95%CI 1.72-1.73) in 2022. Compared with the age, sex and region matched general population, the hazard ratio (HR) adjusted for demographics and clinical characteristics over the follow-up period was 4.07 (95%CI 4.02-4.12) in 2020 decreasing to 1.57 (95%CI 1.56-1.58) in 2022. The HR was highest in the first 30 days in all years. Conclusions: Despite likely underestimation of the fit note rate, we identified a considerable increase among people with COVID-19, even in an era when most people are vaccinated. Most fit notes are associated with the acute phase of the disease, but the increased risk several months post-diagnosis provides further evidence of the long-term impact.

The impact of COVID-19 on medication reviews in English primary care. An OpenSAFELY-TPP analysis of 20 million adult electronic health records. (preprint)

Background The COVID-19 pandemic caused significant disruption to routine activity in primary care. Medication reviews are an important primary care activity to ensure safety and appropriateness of ongoing prescribing and a disruption could have significant negative implications for patient care. Aim Using routinely collected data, our aim was to i) describe the SNOMED CT codes used to report medication review activity ii) report the impact of COVID-19 on the volume and variation of medication reviews. Design and setting With the approval of NHS England, we conducted a cohort study of 20 million adult patient records in general practice, in-situ using the OpenSAFELY platform. Method For each month between April 2019 - March 2022, we report the percentage of patients with a medication review coded monthly and in the previous 12 months. These measures were broken down by regional, clinical and demographic subgroups and amongst those prescribed high risk medications. Results In April 2019, 32.3% of patients had a medication review coded in the previous 12 months. During the first COVID-19 lockdown, monthly activity substantially decreased (-21.1% April 2020), but the rate of patients with a medication review coded in the previous 12 months was not substantially impacted according to our classification (-10.5% March 2021). There was regional and ethnic variation (March 2022 - London 21.9% vs North West 33.6%; Chinese 16.8% vs British 33.0%). Following the introduction of "structured medication reviews", the rate of structured medication review in the last 12 months reached 2.9% by March 2022, with higher percentages in high risk groups (March 2022 - care home residents 34.1%, 90+ years 13.1%, high risk medications 10.2%). The most used SNOMED CT medication review code across the study period was Medication review done - 314530002 (59.5%). Conclusion We have reported a substantial reduction in the monthly rate of medication reviews during the pandemic but rates recovered by the end of the study period.

Impact of COVID-19 on recorded blood pressure screening and hypertension management in England: An analysis of monthly changes in Quality and Outcomes Framework indicators in OpenSAFELY (preprint)

Background: Cardiovascular disease management in primary care in England was disrupted during the COVID-19 pandemic. Objective: We aim to describe the impact of the COVID-19 pandemic on blood pressure screening and hypertension management, based upon a national quality of care scheme (Quality and Outcomes Framework, QOF) across key demographic, regional, and clinical subgroups. To this end, we translate complex clinical quality of care schemes from text descriptions into reusable analytic code. Methods: With the approval of NHS England, a population based cohort study was conducted on 25.2 million patient records in situ using OpenSAFELY-TPP. We included all NHS patients registered at general practices using TPP software between March 2019 and March 2023. Individuals that were eligible for blood pressure screening and with a diagnosis of hypertension were identified according to the QOF 2021/22 business rules. We examined monthly changes in recorded blood pressure screening in the preceding 5 years in patients aged [≥] 45, recorded hypertension prevalence, and the recorded percentage of patients treated to target (i.e., [≤] 140/90 mmHg for patients [≤] 79 years and [≤] 150/90 mmHg for patients [≥] 80 years) in the preceding 12 months, within demographic, regional, and clinical subgroups as well as the variation across practices. Results: The overall percentage of patients aged [≥] 45 who had blood pressure screening recorded in the preceding 5 years decreased from 90% in March 2019 to 85% in March 2023. Recorded hypertension prevalence was relatively stable at 15% throughout the study period. The percentage of patients with a record of hypertension treated to target in the preceding 12 months reduced from a maximum of 71% in March 2020 to a minimum of 47% in February 2021 in patients aged [≤] 79 years, and from 85% in March 2020 to a minimum of 58% in February 2021 in patients aged [≥] 80 years before recovering. Blood pressure screening rates in the preceding 5 years remained stable in older age groups, patients with a record of learning disability, or care home status. Conclusions: There was substantial disruption to hypertension management QOF indicators during the pandemic, which can likely be attributed to a general reduction of blood pressure screening. OpenSAFELY can be used to continuously monitor monthly changes in national quality of care schemes to identify changes in key clinical subgroups early and support prioritisation of recovery from disrupted care caused by COVID-19.

Evaluation of the impact of COVID-19 pandemic on hospital admission related to common infections (preprint)

Background: Antimicrobial resistance (AMR) is a multifaceted global challenge, partly driven by inappropriate antibiotic prescribing. The COVID-19 pandemic impacted antibiotic prescribing for common bacterial infections. This highlights the need to examine risk of hospital admissions related to common infections, excluding COVID-19 infections during the pandemic. Methods: With the approval of NHS England, we accessed electronic health records from The Phoenix Partnership (TPP) through OpenSAFELY platform. We included patients with primary care diagnosis of common infections, including lower respiratory tract infection (LRTI), upper respiratory tract infections (URTI), and lower urinary tract infection (UTI), from January 2019 to August 2022. We excluded patients with a COVID-19 record 90 days before to 30 days after the infection diagnosis. Using Cox proportional-hazard regression models, we predicted risk of infection-related hospital admission in 30 days follow-up period after the diagnosis. Results: We found 12,745,165 infection diagnoses from January 2019 to August 2022. Of them, 80,395 (2.05%) cases were admitted to hospital in the follow-up period. Counts of hospital admission for infections dropped during COVID-19, e.g., LRTI from 3,950 in December 2019 to 520 in April 2020. Comparing those prescribed an antibiotic to those without, reduction in risk of hospital admission were largest with LRTI (adjusted odds ratio (OR) of 0.35; 95% CI, 0.35-0.36) and UTI (adjusted OR 0.45; 95% CI, 0.44-0.46), compared to URTI (adjusted OR 1.04; 95% CI, 1.03-1.06). Conclusion: Large effectiveness of antibiotics in preventing complications related to LRTI and UTI can support better targeting of antibiotics to patients with higher complication risks.

Implementing Germ Defence digital behaviour change intervention via all primary care practices in England to reduce respiratory infections during the COVID-19 pandemic: an efficient cluster randomised controlled trial using the OpenSAFELY platform. (preprint)

Background:  Germ Defence (www.germdefence.org) is an evidence-based interactive website that promotes behaviour change for infection control within households. To maximise the potential of Germ Defence to effectively reduce the spread of COVID-19 the intervention needed to be implemented at scale rapidly. Methods: With the approval of NHS England, we implemented an efficient two-arm (1:1 ratio) cluster randomised controlled trial (RCT) to examine the effectiveness of randomising implementation of Germ Defence via GP practices across England, UK, compared with usual care. GP practices randomised to the intervention arm (n=3292) were emailed and asked to disseminate the Germ Defence intervention to all adult patients via mobile phone text, email or social media. GP practices randomised to the usual care arm (n=3287) maintained standard management for the 4-month trial period after and then asked to share Germ Defence with their adult patients.  The primary outcome was the rate of GP presentations for respiratory tract infections (RTI) per patient. Secondary outcomes comprised rates of acute RTIs, confirmed COVID-19 diagnoses, suspected COVID-19 diagnoses, COVID-19 symptoms, gastrointestinal infection diagnoses, antibiotic usage, hospital admissions.  The impact of the intervention on outcome rates was assessed using negative binomial regression modelling within the OpenSAFELY platform. The uptake of intervention by GP practice, and by patients were measured via website analytics. Results: Germ Defence was used 310,731 times. The average satisfaction score after using the website was 7.52 (0-10 not at all to very satisfied, N = 9933). There was no evidence of a difference in the rate of RTIs between intervention and control practices (rate ratio (RR) 1.01, 95%CI 0.96, 1.06, p=0.70). This was similar to all other eight health outcomes. Patient engagement within intervention arm practices ranged from 0- 48% of a practice list. Practices with high levels of intervention uptake (>11%) had a lower proportion of minority ethnic groups. Conclusions:  We demonstrated that rapid large-scale implementation of a digital behavioural intervention can be evaluated with a novel efficient prospective RCT methodology analysing routinely collected patient data entirely within a trusted research environment. Trial registration: This trial was registered in the ISRCTN registry (14602359) on 12 August 2020.

OpenSAFELY: The impact of COVID-19 on azathioprine, leflunomide, and methotrexate monitoring, and factors associated with change in monitoring rate. (preprint)

Background: The COVID-19 pandemic created unprecedented pressure on healthcare services. This study aimed to investigate if disease-modifying anti-rheumatic drug (DMARD) safety monitoring was affected during the COVID-19 pandemic. Methods: A population-based cohort study was conducted with the approval of NHS England, using the OpenSAFELY platform to access electronic health record data from 24.2 million patients registered at general practices using TPP's SystmOne software. Patients were included for further analysis if prescribed azathioprine, leflunomide, or methotrexate between November 2019 and July 2022. Outcomes were assessed as monthly trends and variation between various sociodemographic and clinical groups for adherence with standard safety monitoring recommendations. Findings: An acute increase in the rate of missed monitoring occurred across the study population (+12.4 percentage points) when lockdown measures were implemented in March 2020. This increase was more pronounced for some patient groups (70-79 year-olds: +13.7 percentage points; females: +12.8 percentage points), regions (North West: +17.0 percentage points), medications (Leflunomide: +20.7 percentage points), and monitoring tests (Blood Pressure: +24.5 percentage points). Missed monitoring rates decreased substantially for all groups by July 2022. Substantial and consistent differences were observed in overall missed monitoring rates between several groups throughout the study. Interpretation: DMARD monitoring rates temporarily deteriorated during the COVID-19 pandemic. Deterioration coincided with the onset of lockdown measures, with monitoring rates recovering rapidly as lockdown measures were eased. Differences observed in monitoring rates between medications, tests, regions, and patient groups, highlight opportunities to tackle potential inequalities in the provision or uptake of monitoring services. Further research should aim to evaluate the causes of the differences identified between groups. Funding: None. Keywords COVID-19, electronic health records, general practice, primary health care, antirheumatic agents, methotrexate, azathioprine, leflunomide.

Primary Care Post-COVID syndrome Diagnosis and Referral Coding (preprint)

Introduction - Guidelines for diagnosing and managing Post-COVID syndrome have been rapidly developed. Consistency of the application of these guidelines in primary care is unknown. Electronic health records provide an opportunity to review the use of codes relating to Post-COVID syndrome. This paper explores the use of primary care records as a surrogate uptake measure for NICEs rapid guideline managing the long-term effects of COVID-19 by measuring the use of Post-COVID syndrome diagnosis and referral codes in the pathway. Method - With the approval of NHS England we used routine clinical data from the OpenSafely-EMIS/-TPP platforms. Counts of Post-COVID syndrome diagnosis and referral codes were generated from a cohort of all adults, establishing numbers of diagnoses and referrals following diagnosis. The relationship between Post-COVID syndrome diagnosis and referral codes was explored with reference to NICEs rapid guideline. Results - Of over 45 million patients, 69,220 (0.15%) had a Post-COVID syndrome diagnostic code, and 67,741 (0.15%) had a referral code. 78% of referral codes did not have an associated diagnosis code. 79% of diagnosis codes had no subsequent referral code. Only 18,633 (0.04%) had both. There were higher rates of both diagnosis and referral in those who were more deprived, female and some ethnic groups. Discussion - This study demonstrates variation in diagnosis and referral coding rates for Post-COVID syndrome across different patient groups. The results, with limited crossover of referral and diagnostic codes, suggest only one type of code is usually recorded. Recording one code limits the use of routine data for monitoring Post-COVID syndrome diagnosis and management, but suggests several areas for improvement in coding. Post-COVID syndrome coding, particularly diagnosis coding, needs to improve before administrators and researchers can use it to evaluate care pathways.

Trends in weight gain recorded in English primary care before and during the Coronavirus-19 pandemic: an observational cohort study using the OpenSAFELY platform (preprint)

Background We investigated which clinical and sociodemographic characteristics were associated with unhealthy patterns of weight gain amongst adults living in England during the pandemic. Methods With the approval of NHS England we conducted an observational cohort study of Body Mass Index (BMI) changes between March 2015 and March 2022 using the OpenSAFELY-TPP platform. We estimated individual rates of weight gain before and during the pandemic, and identified individuals with rapid weight gain (>0.5kg/m2/year) in each period. We also estimated the change in rate of weight gain between the prepandemic and pandemic period and defined extreme-accelerators as the ten percent of individuals with the greatest increase (>1.84kg/m2/year). We estimated associations with these outcomes using multivariate logistic regression. Findings We extracted data on 17,742,365 adults (50.1% female, 76.1% White British). Median BMI increased from 27.8kg/m2[IQR:24.3 to 32.1] in 2019 (March 2019 to February 2020) to 28.0kg/m2 [24.4 to 32.6] in 2021. Rapid pandemic weight gain (n=3,214,155) was associated with female sex (male vs female: aOR 0.76 [95%CI:0.76 to 0.76]); younger age (50 to 59 years vs 18 to 29 years: aOR 0.60 [0.60 to 0.61]); White British ethnicity (Black Caribbean vs White British: aOR 0.91 [0.89 to 0.94]); deprivation (least-deprived-IMD-quintile vs most-deprived:aOR 0.77 [0.77 to 0.78]); and long-term conditions, of which mental health conditions had the greatest effect (e.g. depression (aOR 1.18[1.17 to 1.18])). Similar characteristics increased risk of extreme acceleration (n=2,768,695). Interpretation We found female sex, younger age, deprivation and mental health conditions increased risk of unhealthy patterns of pandemic weight gain. This highlights the need to incorporate sociodemographic, physical, and mental health characteristics when formulating post-pandemic research, policies, and interventions targeting BMI. Funding NIHR

Living alone and mental health: parallel analyses in longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic (preprint)

Objectives: To describe the mental health gap between those who live alone and those who live with others, and to examine whether the COVID-19 pandemic had an impact on this gap. Design: Ten population based prospective cohort studies, and a retrospective descriptive cohort study based on electronic health records (EHRs). Setting: UK Longitudinal population-based surveys (LPS), and primary and secondary care records within the OpenSAFELY-TPP database. Participants: Participants from the LPS were included if they had information on living status in early 2020, valid data on mental ill-health at the closest pre-pandemic assessment and at least once during the pandemic, and valid data on a key minimum set of covariates. The EHR dataset included 16 million adults registered with primary care practices in England using TPP SystmOne software on 1st February 2020, with at least three months of registration, valid address data, and living in households of <16 people. Main outcome measures: In the LPS, self-reported survey measures of psychological distress and life satisfaction were assessed in the nearest pre-pandemic sweep and three periods during the pandemic: April-June 2020, July-October 2020, and November 2020-March 2021. In the EHR analyses, outcomes were morbidity codes recorded in primary or secondary care between March 2018 and January 2022 reflecting the diagnoses of depression, self-harm, anxiety, obsessive compulsive disorder, eating disorders, and severe mental illnesses. Results: The LPS consisted of 37,544 participants (15.2% living alone) and we found greater psychological distress (SMD: 0.09 (95% CI: 0.04, 0.14) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30, -0.15) in those living alone pre-pandemic, and the gap between the two groups stayed similar after the onset of the pandemic. In the EHR analysis of almost 16 million records (21.4% living alone), codes indicating mental health conditions were more common in those who lived alone compared to those who lived with others (e.g., depression 26 and severe mental illness 58 cases more per 100,000). Recording of mental health conditions fell during the pandemic for common mental health disorders and the gap between the two groups narrowed. Conclusions: Multiple sources of data indicate that those who live alone experience greater levels of common and severe mental illnesses, and lower life satisfaction. During the pandemic this gap in need remained, however, there was a narrowing of the gap in service use, suggesting greater barriers to healthcare access for those who live alone.